Abstract
In this paper, an output-feedback direct adaptive fuzzy neural controller for an anti-lock braking system (ABS) is developed. It is assumed that only the system output, the wheel slip ratio, is available for measurement. The main control strategy is to force the wheel slip ratio tracking variant optimal slip ratios, which may vary with the environment and assumed to be known during the vehicle-stopping period. By using the strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. To demonstrate the effectiveness of the proposed method, simulation results are illustrated.
| Original language | English |
|---|---|
| Pages (from-to) | 3675-3680 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 4 |
| Publication status | Published - 2003 |
| Externally published | Yes |
| Event | System Security and Assurance - Washington, DC, United States Duration: 2003 Oct 5 → 2003 Oct 8 |
Keywords
- Anti-lock brake system
- Fuzzy neural control
- Tracking optimal slip ratios
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture